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Experimental evidence indicates that exposure to certain pollutants is associated with liver damage. Per- and polyfluoroalkyl substances (PFAS) are persistent synthetic chemicals widely used in industry and consumer products and bioaccumulate in food webs and human tissues, such as the liver. The objective of this study was to conduct a systematic review of the literature and meta-analysis evaluating PFAS exposure and evidence of liver injury from rodent and epidemiological studies. PubMed and Embase were searched for all studies from earliest available indexing year through 1 December 2021 using keywords corresponding to PFAS exposure and liver injury. For data synthesis, results were limited to studies in humans and rodents assessing the following indicators of liver injury: serum alanine aminotransferase (ALT), nonalcoholic fatty liver disease, nonalcoholic steatohepatitis, or steatosis. For human studies, at least three observational studies per PFAS were used to conduct a weighted -score meta-analysis to determine the direction and significance of associations. For rodent studies, data were synthesized to qualitatively summarize the direction and significance of effect. Our search yielded 85 rodent studies and 24 epidemiological studies, primarily of people from the United States. Studies focused primarily on legacy PFAS: perfluorooctanoic acid (PFOA), perfluorooctanesulfonic acid (PFOS), perfluorononanoic acid (PFNA), and perfluorohexanesulfonic acid. Meta-analyses of human studies revealed that higher ALT levels were associated with exposure to PFOA ( 6.20, ), PFOS ( 3.55, ), and PFNA ( 2.27, ). PFOA exposure was also associated with higher aspartate aminotransferase and gamma-glutamyl transferase levels in humans. In rodents, PFAS exposures consistently resulted in higher ALT levels and steatosis. There is consistent evidence for PFAS hepatotoxicity from rodent studies, supported by associations of PFAS and markers of liver function in observational human studies. This review identifies a need for additional research evaluating next-generation PFAS, mixtures, and early life exposures. https://doi.org/10.1289/EHP10092.

Exposure to per- and polyfluoroalkyl substances (PFAS) is ubiquitous and has been associated with an increased risk of several cardiometabolic diseases. However, the metabolic pathways linking PFAS exposure and human disease are unclear. We examined associations of PFAS mixtures with alterations in metabolic pathways in independent cohorts of adolescents and young adults. Three hundred twelve overweight/obese adolescents from the Study of Latino Adolescents at Risk (SOLAR) and 137 young adults from the Southern California Children's Health Study (CHS) were included in the analysis. Plasma PFAS and the metabolome were determined using liquid-chromatography/high-resolution mass spectrometry. A metabolome-wide association study was performed on log-transformed metabolites using Bayesian regression with a g-prior specification and g-computation for modeling exposure mixtures to estimate the impact of exposure to a mixture of six ubiquitous PFAS (PFOS, PFHxS, PFHpS, PFOA, PFNA, and PFDA). Pathway enrichment analysis was performed using Mummichog and Gene Set Enrichment Analysis. Significance across cohorts was determined using weighted -tests. In the SOLAR and CHS cohorts, PFAS exposure was associated with alterations in tyrosine metabolism (meta-analysis ) and fatty acid biosynthesis ( ), among others. For example, when increasing all PFAS in the mixture from low ( th percentile) to high ( th percentile), thyroxine (T4), a thyroid hormone related to tyrosine metabolism, increased by 0.72 standard deviations (SDs; equivalent to a standardized mean difference) in the SOLAR cohort (95% Bayesian credible interval (BCI): 0.00, 1.20) and 1.60 SD in the CHS cohort (95% BCI: 0.39, 2.80). Similarly, when going from low to high PFAS exposure, arachidonic acid increased by 0.81 SD in the SOLAR cohort (95% BCI: 0.37, 1.30) and 0.67 SD in the CHS cohort (95% BCI: 0.00, 1.50). In general, no individual PFAS appeared to drive the observed associations. Exposure to PFAS is associated with alterations in amino acid metabolism and lipid metabolism in adolescents and young adults. https://doi.org/10.1289/EHP11372.

Exposure to per- and polyfluoroalkyl substances (PFAS), a prevalent class of persistent pollutants, may increase the risk of type 2 diabetes. We examined associations between PFAS exposure and glucose metabolism in youth. Overweight/obese adolescents from the Study of Latino Adolescents at Risk of Type 2 Diabetes (SOLAR; ) participated in annual visits for an average of . Generalizability of findings were tested in young adults from the Southern California Children's Health Study (CHS; ) who participated in a clinical visit with a similar protocol. At each visit, oral glucose tolerance tests were performed to estimate glucose metabolism and function via the insulinogenic index. Four PFAS were measured at baseline using liquid chromatography-high-resolution mass spectrometry; high levels were defined as concentrations percentile. In females from the SOLAR, high perfluorohexane sulfonate (PFHxS) levels ( ) were associated with the development of dysregulated glucose metabolism beginning in late puberty. The magnitude of these associations increased postpuberty and persisted through 18 years of age. For example, postpuberty, females with high PFHxS levels had higher 60-min glucose (95% CI: ; ), higher 2-h glucose (95% CI: ; ), and 25% lower function ( ) compared with females with low levels. Results were largely consistent in the CHS, where females with elevated PFHxS levels had higher 60-min glucose (95% CI: ; ) and higher 2-h glucose, which did not meet statistical significance (95% CI: ; ). In males, no consistent associations between PFHxS and glucose metabolism were observed. No consistent associations were observed for other PFAS and glucose metabolism. Youth exposure to PFHxS was associated with dysregulated glucose metabolism in females, which may be due to changes in function. These associations appeared during puberty and were most pronounced postpuberty. https://doi.org/10.1289/EHP9200.

Prostate-specific antigen (PSA) screening for prostate cancer remains controversial because it increases overdiagnosis and overtreatment of clinically insignificant tumors. Accounting for genetic determinants of constitutive, non-cancer-related PSA variation has potential to improve screening utility. In this study, we discovered 128 genome-wide significant associations ( P  < 5 × 10 −8 ) in a multi-ancestry meta-analysis of 95,768 men and developed a PSA polygenic score (PGS PSA ) that explains 9.61% of constitutive PSA variation. We found that, in men of European ancestry, using PGS-adjusted PSA would avoid up to 31% of negative prostate biopsies but also result in 12% fewer biopsies in patients with prostate cancer, mostly with Gleason score <7 tumors. Genetically adjusted PSA was more predictive of aggressive prostate cancer (odds ratio (OR) = 3.44, P  = 6.2 × 10 −14 , area under the curve (AUC) = 0.755) than unadjusted PSA (OR = 3.31, P  = 1.1 × 10 −12 , AUC = 0.738) in 106 cases and 23,667 controls. Compared to a prostate cancer PGS alone (AUC = 0.712), including genetically adjusted PSA improved detection of aggressive disease (AUC = 0.786, P  = 7.2 × 10 −4 ). Our findings highlight the potential utility of incorporating PGS for personalized biomarkers in prostate cancer screening. Analyses of large population-based cohorts and clinical trials show that using polygenic scores to account for variability in PSA levels improves detection of prostate cancer, suggesting an approach for enhancing screening accuracy.

Christopher Haiman, Bogdan Pasaniuc, David Reich and colleagues report a major role for low-frequency variation in the risk for prostate cancer. They show that alleles with >1% minor allele frequency contribute an order of magnitude more to risk for prostate cancer than these alleles do to overall genetic variation. We report targeted sequencing of 63 known prostate cancer risk regions in a multi-ancestry study of 9,237 men and use the data to explore the contribution of low-frequency variation to disease risk. We show that SNPs with minor allele frequencies (MAFs) of 0.1–1% explain a substantial fraction of prostate cancer risk in men of African ancestry. We estimate that these SNPs account for 0.12 (standard error (s.e.) = 0.05) of variance in risk (∼42% of the variance contributed by SNPs with MAF of 0.1–50%). This contribution is much larger than the fraction of neutral variation due to SNPs in this class, implying that natural selection has driven down the frequency of many prostate cancer risk alleles; we estimate the coupling between selection and allelic effects at 0.48 (95% confidence interval [0.19, 0.78]) under the Eyre-Walker model. Our results indicate that rare variants make a disproportionate contribution to genetic risk for prostate cancer and suggest the possibility that rare variants may also have an outsize effect on other common traits.

The objective of this study was to use available data on the prevalence of COVID-19 risk factors in subpopulations and epidemic dynamics at the population level to estimate probabilities of severe illness and the case and infection fatality rates (CFR and IFR) stratified across subgroups representing all combinations of the risk factors age, comorbidities, obesity, and smoking status. We focus on the first year of the epidemic in Los Angeles County (LAC) (March 1, 2020–March 1, 2021), spanning three epidemic waves. A relative risk modeling approach was developed to estimate conditional effects from available marginal data. A dynamic stochastic epidemic model was developed to produce time-varying population estimates of epidemic parameters including the transmission and infection observation rate. The epidemic and risk models were integrated to produce estimates of subpopulation-stratified probabilities of disease progression and CFR and IFR for LAC. The probabilities of disease progression and CFR and IFR were found to vary as extensively between age groups as within age categories combined with the presence of absence of other risk factors, suggesting that it is inappropriate to summarize epidemiological parameters for age categories alone, let alone the entire population. The fine-grained subpopulation-stratified estimates of COVID-19 outcomes produced in this study are useful in understanding disparities in the effect of the epidemic on different groups in LAC, and can inform analyses of targeted subpopulation-level policy interventions.

Background Child blood pressure (BP) is predictive of future cardiovascular risk. Prenatal exposure to metals has been associated with higher BP in childhood, but most studies have evaluated elements individually and measured BP at a single time point. We investigated impacts of prenatal metal mixture exposures on longitudinal changes in BP during childhood and elevated BP at 11 years of age. Methods The current study included 176 mother-child pairs from the Rhea Study in Heraklion, Greece and focused on eight elements (antimony, arsenic, cadmium, cobalt, lead, magnesium, molybdenum, selenium) measured in maternal urine samples collected during pregnancy (median gestational age at collection: 12 weeks). BP was measured at approximately 4, 6, and 11 years of age. Covariate-adjusted Bayesian Varying Coefficient Kernel Machine Regression and Bayesian Kernel Machine Regression (BKMR) were used to evaluate metal mixture impacts on baseline and longitudinal changes in BP (from ages 4 to 11) and the development of elevated BP at age 11, respectively. BKMR results were compared using static versus percentile-based cutoffs to define elevated BP. Results Molybdenum and lead were the mixture components most consistently associated with BP. J-shaped relationships were observed between molybdenum and both systolic and diastolic BP at age 4. Similar associations were identified for both molybdenum and lead in relation to elevated BP at age 11. For molybdenum concentrations above the inflection points (~ 40–80 μg/L), positive associations with BP at age 4 were stronger at high levels of lead. Lead was positively associated with BP measures at age 4, but only at high levels of molybdenum. Potential interactions between molybdenum and lead were also identified for BP at age 11, but were sensitive to the cutoffs used to define elevated BP. Conclusions Prenatal exposure to high levels of molybdenum and lead, particularly in combination, may contribute to higher BP at age 4. These early effects appear to persist throughout childhood, contributing to elevated BP in adolescence. Future studies are needed to identify the major sources of molybdenum and lead in this population.

Childhood obesity poses a significant public health challenge, yet the molecular intricacies underlying its pathobiology remain elusive. Leveraging extensive multi-omics profiling (methylome, miRNome, transcriptome, proteins and metabolites) and a rich phenotypic characterization across two parts of Europe within the population-based Human Early Life Exposome project, we unravel the molecular landscape of childhood obesity and associated metabolic dysfunction. Our integrative analysis uncovers three clusters of children defined by specific multi-omics profiles, one of which characterized not only by higher adiposity but also by a high degree of metabolic complications. This high-risk cluster exhibits a complex interplay across many biological pathways, predominantly underscored by inflammation-related cascades. Further, by incorporating comprehensive information from the environmental risk-scape of the critical pregnancy period, we identify pre-pregnancy body mass index and environmental pollutants like perfluorooctanoate and mercury as important determinants of the high-risk cluster. Overall, our work helps to identify potential risk factors for prevention and intervention strategies early in the life course aimed at mitigating obesity and its long-term health consequences. Obesity encompasses numerous interconnected pathological mechanisms. Here, the authors show that integrating multi-omics data uncovers distinct molecular profiles and prenatal factors linked to childhood obesity and metabolic dysfunction, providing insights for early prevention and intervention strategies.

BackgroundProstate cancer (PrCa) demonstrates a heterogeneous clinical presentation ranging from largely indolent to lethal. We sought to identify a signature of rare inherited variants that distinguishes between these two extreme phenotypes.MethodsWe sequenced germline whole exomes from 139 aggressive (metastatic, age of diagnosis < 60) and 141 non-aggressive (low clinical grade, age of diagnosis ≥60) PrCa cases. We conducted rare variant association analyses at gene and gene set levels using SKAT and Bayesian risk index techniques. GO term enrichment analysis was performed for genes with the highest differential burden of rare disruptive variants.ResultsProtein truncating variants (PTVs) in specific DNA repair genes were significantly overrepresented among patients with the aggressive phenotype, with BRCA2, ATM and NBN the most frequently mutated genes. Differential burden of rare variants was identified between metastatic and non-aggressive cases for several genes implicated in angiogenesis, conferring both deleterious and protective effects.ConclusionsInherited PTVs in several DNA repair genes distinguish aggressive from non-aggressive PrCa cases. Furthermore, inherited variants in genes with roles in angiogenesis may be potential predictors for risk of metastases. If validated in a larger dataset, these findings have potential for future clinical application.

Background Ultra-processed foods (UPFs), often high in sodium, sugar, and unhealthy fats, compose more than half of total dietary energy consumption in the United States. A diet composed of a high amount of UPFs can contribute to glucose dysregulation and insulin resistance, which may lead to prediabetes and type 2 diabetes (T2D). However, few studies have assessed the associations between UPFs and T2D or obesity in young people. The goal of this study is to examine associations between UPF consumption and prediabetes and related biomarkers in youth. Methods Young adults (age 17–22, n  = 85) with a history of overweight or obesity from the Metabolic and Asthma Incidence Research (Meta-AIR) study, a subset of the Children’s Health Study, were enrolled between 2014 and 2018 and returned for a second visit between 2020 and 2022. Participants completed two 24-hour dietary recalls and an oral glucose tolerance test at each visit. Food items were categorized as either an UPF or non-UPF according to NOVA classification guidelines. The proportion of the diet composed of UPFs was calculated for each participant. Regression models were used to assess relationships of UPF consumption at baseline and change between visits with markers of glucose homeostasis at follow-up, adjusting for demographics, physical activity, and total energy intake. Results A 10%-point increase in UPF consumption between visits was associated with a 51% (OR: 1.51, 95% Cl: 1.04, 2.31) higher odds of having prediabetes and 158% (OR: 2.58, 95% CI: 1.43, 5.85) higher odds of impaired glucose tolerance at follow-up. Higher baseline UPF consumption was significantly positively associated with 2-hour insulin ( = 45.11, 95% CI: 22.42, 67.80) and insulin area under the curve ( = 63.56, 95% CI: 34.95, 92.17) at follow-up. Conclusion UPF consumption may increase the risk for T2D among young adults. Our findings suggest that limiting UPF consumption could be an important strategy for T2D prevention in this population.